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| END4025 | Meta Heuristic Methods | 3+0+0 | ECTS:5 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Elective | | Department | DEPARTMENT of INDUSTRIAL ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Group study, Practical | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Dr. Öğr. Üyesi Kemal ÇAKAR | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | A large part of the research area of industrial engineering includes NP-hard problems. These problems usually can not be solved by exact optimization techniques. In recent years, heuristic techniques will be effectively deal with these problems. In this course, heuristic techniques and its application areas will be introduced. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Student learns the basic concepts of heuristic methods | 2 | 1,3 | | LO - 2 : | Student gains the ability of identificating problems and finding solutions by using a mathematical model | 5 | 1,3 | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Introduction to Optimization problems, NP-Complete problems, , Meta-heuristic Methods (Genetic Algorithms, Tabu Search, Simulated Annealing, Ant Colony) |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction to Optimization | | | Week 2 | Optimization Methods | | | Week 3 | Metaheuristic Methods | | | Week 4 | Simulated Annealing Part 1 | | | Week 5 | Simulated Annealing Part 2 | | | Week 6 | Simulated Annealing Part 3 | | | Week 7 | Genetic Algorithms Part 1 | | | Week 8 | Mid-term Exam | | | Week 9 | Genetic Algorithms Part 2 | | | Week 10 | Genetic Algorithms Part 3 | | | Week 11 | Tabu Search Algorithms Part 1 | | | Week 12 | Tabu Search Algorithms Part 2 | | | Week 13 | Ant Colony Optimization Algorithm Part 1 | | | Week 14 | Ant Colony Optimization Algorithm Part 2 | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 8 | 09/12/2020 | 3 | 30 | | Homework/Assignment/Term-paper | 15 | 20/01/2021 | 3 | 20 | | End-of-term exam | 16 | 03/02/2021 | 3 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 3 | 12 | 36 | | Arasınav için hazırlık | 10 | 1 | 10 | | Arasınav | 1.5 | 1 | 1.5 | | Ödev | 4 | 3 | 12 | | Dönem sonu sınavı için hazırlık | 10 | 2 | 20 | | Dönem sonu sınavı | 1.5 | 1 | 1.5 | | Total work load | | | 123 |
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